The Parallelism Motifs of Genomic Data Analysis

Genomic data sets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and share this data with the research community, but some of these genomic data analysis problems require large scale computational platforms to meet both the memory and computational requirements. These applications differ from scientific simulations that dominate the workload on high end parallel systems today and place different requirements on programming support, software libraries, and parallel architectural design. For example, they involve irregular communication patterns such as asynchronous updates to shared data structures. We consider several problems in high performance genomics analysis, including alignment, profiling, clustering, and assembly for both single genomes and metagenomes. We identify some of the common computational patterns or motifs that help inform parallelization strategies and compare our motifs to some of the established lists, arguing that at least two key patterns, sorting and hashing, are missing

Enhanced fold recognition using efficient short fragment clustering

The main structure aligner in the CCP4 Software Suite, SSM (Secondary Structure Matching) has a limited applicability on the intermediate stages of the structure solution process, when the secondary structure cannot be reliably computed due to structural incompleteness or a fragmented mainchain. In this study, we describe a new algorithm for the alignment and comparison of protein structures in CCP4, which was designed to overcome SSM's limitations but retain its quality and speed. The new algorithm, named GESAMT (General Efficient Structural Alignment of Macromolecular Targets), employs the old idea of deriving the global structure similarity from a promising set of locally similar short fragments, but uses a few technical solutions that make it considerably faster. A comparative sensitivity and selectivity analysis revealed an unexpected significant improvement in the fold recognition properties of the new algorithm, which also makes it useful for applications in the structural bioinformatics domain. The new tool is included in the CCP4 Software Suite starting from version 6.3

Chemoinformatics Research at the University of Sheffield: A History and Citation Analysis

This paper reviews the work of the Chemoinformatics Research Group in the Department of Information Studies at the University of Sheffield, focusing particularly on the work carried out in the period 1985-2002. Four major research areas are discussed, these involving the development of methods for: substructure searching in databases of three-dimensional structures, including both rigid and flexible molecules; the representation and searching of the Markush structures that occur in chemical patents; similarity searching in databases of both two-dimensional and three-dimensional structures; and compound selection and the design of combinatorial libraries. An analysis of citations to 321 publications from the Group shows that it attracted a total of 3725 residual citations during the period 1980-2002. These citations appeared in 411 different journals, and involved 910 different citing organizations from 54 different countries, thus demonstrating the widespread impact of the Group's work

Fold Recognition via a Tree

Recently, we developed a pairwise structural alignment algorithm using realistic structural and environmental information (SAUCE). In this paper, we at first present an automatic fold hierarchical classification based on SAUCE alignments. This classification enables us to build a fold tree containing different levels of multiple structural profiles. Then a tree-based fold search algorithm is described. We applied this method to a group of structures with sequence identity less than 35% and did a series of leave one out tests. These tests are approximately comparable to fold recognition tests on superfamily level. Results show that fold recognition via a fold tree can be faster and better at detecting distant homologues than classic fold recognition methods.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63155/1/cmb.2006.13.1565.pd

Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information

Janssen S, McDonald D, Gonzalez A, et al. Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information. mSystems. 2018;3(3):e00021-18

Revisión de los métodos computerizados para la reconstrucción de fragmentos arqueológicos de cerámica

[ES] Las cerámicas son los hallazgos más numerosos encontrados en las excavaciones arqueológicas; a menudo se usan para obtener información sobre la historia, la economía y el arte de un sitio. Los arqueólogos rara vez encuentran jarrones completos; en general, están dañados y en fragmentos, a menudo mezclados con otros grupos de cerámica.El análisis y la reconstrucción de fragmentos se realiza por un operador experto mediante el uso del método manual tradicional. Los artículos revisados proporcionaron evidencias de que el método tradicional no es reproducible, no es repetible, consume mucho tiempo y sus resultados generan grandes incertidumbres. Con el objetivo de superar los límites anteriores, en los últimos años, los investigadores han realizado esfuerzos para desarrollar métodos informáticos que permitan el análisis de fragmentos arqueológicos de cerámica, todo ello destinado a su reconstrucción. Para contribuir a este campo de estudio, en este artículo, se presenta un análisis exhaustivo de las publicaciones disponibles más importantes hasta finales de 2019. Este estudio, centrado únicamente en fragmentos de cerámica, se realiza mediante la recopilación de artículos en inglés de la base de datos Scopus, utilizando las siguientes palabras clave: "métodos informáticos en arqueología", "arqueología 3D", "reconstrucción 3D", "reconocimiento y reconstrucción automática de características", "restauración de reliquias en forma de cerámica ". La lista se completa con referencias adicionales que se encuentran a través de la lectura de documentos seleccionados. Los 53 trabajos seleccionados se dividen en tres períodos de tiempo. Según una revisión detallada de los estudios realizados, los elementos clave de cada método analizado se enumeran en función de las herramientas de adquisición de datos, las características extraídas, los procesos de clasificación y las técnicas de correspondencia. Finalmente, para superar las brechas reales, se proponen algunas recomendaciones para futuras investigaciones.[EN] Potteries are the most numerous finds found in archaeological excavations; they are often used to get information about the history, economy, and art of a site. Archaeologists rarely find complete vases but, generally, damaged and in fragments, often mixed with other pottery groups. By using the traditional manual method, the analysis and reconstruction of sherds are performed by a skilled operator. Reviewed papers provided evidence that the traditional method is not reproducible, not repeatable, time-consuming and its results have great uncertainties. To overcome the aforementioned limits, in the last years, researchers have made efforts to develop computer-based methods for archaeological ceramic sherds analysis, aimed at their reconstruction. To contribute to this field of study, in this paper, a comprehensive analysis of the most important available publications until the end of 2019 is presented. This study, focused on pottery fragments only, is performed by collecting papers in English by the Scopus database using the following keywords: “computer methods in archaeology", "3D archaeology", "3D reconstruction", "automatic feature recognition and reconstruction", "restoration of pottery shape relics”. The list is completed by additional references found through the reading of selected papers. The 53 selected papers are divided into three periods of time. According to a detailed review of the performed studies, the key elements of each analyzed method are listed based on data acquisition tools, features extracted, classification processes, and matching techniques. Finally, to overcome the actual gaps some recommendations for future researches are proposed.Highlights:The traditional manual method for reassembling sherds is very time-consuming and costly; it also requires a great deal effort from skilled archaeologists in repetitive and routine activities.Computer-based methods for archaeological ceramic sherds reconstruction can help archaeologists in the above-mentioned repetitive and routine activities.In this paper, the state-of-the-art computer-based methods for archaeological ceramic sherds reconstruction are reviewed, and some recommendations for future researches are proposed.Eslami, D.; Di Angelo, L.; Di Stefano, P.; Pane, C. (2020). Review of computer-based methods for archaeological ceramic sherds reconstruction. 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International Journal of Computational Methods in Heritage Science, 3(1), 20-32. https://doi.org/10.4018/ijcmhs.2019010102Kampel, M., & Sablatnig, R. (2003). Profile-based Pottery Reconstruction. In IEEE Proceeding of Conference on Computer Vision and Pattern Recognition Workshops, Wisconsin, June, (pp. 1-6). https://doi.org/10.1109/CVPRW.2003.10007Kampel, M, & Mara, H. (2005). Robust 3D reconstruction of archaeological pottery based on concentric circular rills. In Proceedings of the Sixth International. Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS'05), Montreux, Switzerland, (pp. 14-20). Retrieved from https://semanticscholar.org/43df/9b3c6fef5aa54964bdc4825a86cc4e9f4531Kampel, M., & Sablatnig, R. (2003). An automated pottery archival and reconstruction system. Journal of Visualization and Computer Animation, 14(3), 111-120. https://doi.org/10.1002/vis.310Kampel, M., & Sablatnig, R. (2004). 3D Puzzling of Archeological Fragments. In Proceedings of 9th Computer Vision Winter Workshop, (February), (pp. 31-40). Retrieved from https://cvl.tuwien.ac.at/wp-content/uploads/2014/12/cvww041Karasik, A., & Smilansky, U. (2011). Computerized morphological classification of ceramics. Journal of Archaeological Science, 38(10), 2644-2657. https://doi.org/10.1016/j.jas.2011.05.023Kashihara, K. (2012). Three-dimensional reconstruction of artifacts based on a hybrid genetic algorithm. In IEEE International Conference on Systems, Man and Cybernetics, (pp. 900-905). https://doi.org/10.1109/ICSMC.2012.6377842Kashihara, K. (2017). An intelligent computer assistance system for artifact restoration based on genetic algorithms with plane image features. International Journal of Computational Intelligence and Applications, 16(3), 1-15. https://doi.org/10.1142/S1469026817500213Kleber, F., & Sablatnig, R. (2009). A survey of techniques for document and archaeology artifact reconstruction. In Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, (March 2014), (pp. 1061-1065). https://doi.org/10.1109/ICDAR.2009.154Kotoula, E. (2016). Semiautomatic fragments matching and virtual reconstruction: a case study on ceramics. International Journal of Conservation Science, 7(1), 71-86. Retrieved from http://eprints.lincoln.ac.uk/id/eprint/31035/Lucena, M., Martínez-Carrillo, A. L., Fuertes, J. M., Javier Carrascosa Malagón, F., & Ruiz Rodríguez, A. (2016). Decision support system for classifying archaeological pottery profiles based on mathematical morphology. Multimedia Tools and Applications, 75(7), 3677-3691. https://doi.org/10.1007/s11042-014-2063-6Maiza, C., & Gaildrat, V. (2005). Automatic classification of archaeological potsherds. 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H., Nados, W. L., & Maaroof, M. K. A. (2017). Classification archaeological fragments into groups. Research Journal of Applied Sciences, Engineering, and Technology, 14(9), 324-333. https://doi.org/10.19026/rjaset.14.5072Sablatnig, R., & Menard, C. (1997). 3D Reconstruction of Archaeological Pottery using Profile Primitives. In Proceedings of I International Workshop on Synthetic-Natural Hybrid Coding and Three-Dimensional Imaging, (pp. 93-96).Sablatnig, R., Menard, C., & Kropatseh, W. (1998). Classification of archaeological fragments using a description language. In Proceedings of European Signal Processing Conference, (Eusipco '98), (pp. 1097-1100), 1998.Sakpere, W. (2019). 3D Reconstruction of Archaeological Pottery from Its Point Cloud. In Proceedings of Iberian Conference on Pattern Recognition and Image Analysis, (pp. 125-136). https://doi.org/10.1007/978-3-030-31332-6_11Shin, H., Doumas, C., Funkhouser, T., Rusinkiewicz, S., Steiglitz, K.,Vlachopoulos, & Weyrich, T. (2010). 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Some studies on protein structure alignment algorithms

The alignment of two protein structures is a fundamental problem in structural bioinformatics.Their structural similarity carries with it the connotation of similar functional behavior that couldbe exploited in various applications. A plethora of algorithms, including one by us, is a testamentto the importance of the problem. In this thesis, we propose a novel approach to measure theeectiveness of a sample of four such algorithms, DALI, TM-align, CE and EDAlignsse, for de-tecting structural similarities among proteins. The underlying premise is that structural proximityshould translate into spatial proximity. To verify this, we carried out extensive experiments withve dierent datasets, each consisting of proteins from two to six dierent families.In further addition to our work, we have focused on the area of computational methods foraligning multiple protein structures. This problem is known for its np-complete nature. Therefore,there are many ways to come up with a solution which can be better than the existing ones or atleast as good as them. Such a solution is presented here in this thesis. We have used a heuristicalgorithm which is the Progressive Multiple Alignment approach, to have the multiple sequencealignment. We used the root mean square deviation (RMSD) as a measure of alignment quality andreported this measure for a large and varied number of alignments. We also compared the executiontimes of our algorithm with the well-known algorithm MUSTANG for all the tested alignments